/*
 *   This program is free software: you can redistribute it and/or modify
 *   it under the terms of the GNU General Public License as published by
 *   the Free Software Foundation, either version 3 of the License, or
 *   (at your option) any later version.
 *
 *   This program is distributed in the hope that it will be useful,
 *   but WITHOUT ANY WARRANTY; without even the implied warranty of
 *   MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
 *   GNU General Public License for more details.
 *
 *   You should have received a copy of the GNU General Public License
 *   along with this program.  If not, see <http://www.gnu.org/licenses/>.
 */

/*
 *    AbstractDensityBasedClusterer.java
 *    Copyright (C) 1999-2012 University of Waikato, Hamilton, New Zealand
 *
 */

package weka.clusterers;

import weka.core.Instance;
import weka.core.SerializedObject;
import weka.core.Utils;

/**
 * Abstract clustering model that produces (for each test instance) an estimate
 * of the membership in each cluster (ie. a probability distribution).
 *
 * @author Mark Hall (mhall@cs.waikato.ac.nz)
 * @author Eibe Frank (eibe@cs.waikato.ac.nz)
 * @version $Revision$
 */
public abstract class AbstractDensityBasedClusterer extends AbstractClusterer implements DensityBasedClusterer {

    /** for serialization. */
    private static final long serialVersionUID = -5950728041704213845L;

    // ===============
    // Public methods.
    // ===============

    /**
     * Returns the prior probability of each cluster.
     *
     * @return the prior probability for each cluster
     * @exception Exception if priors could not be returned successfully
     */
    public abstract double[] clusterPriors() throws Exception;

    /**
     * Computes the log of the conditional density (per cluster) for a given
     * instance.
     * 
     * @param instance the instance to compute the density for
     * @return an array containing the estimated densities
     * @exception Exception if the density could not be computed successfully
     */
    public abstract double[] logDensityPerClusterForInstance(Instance instance) throws Exception;

    /**
     * Computes the density for a given instance.
     * 
     * @param instance the instance to compute the density for
     * @return the density.
     * @exception Exception if the density could not be computed successfully
     */
    public double logDensityForInstance(Instance instance) throws Exception {

        double[] a = logJointDensitiesForInstance(instance);
        double max = a[Utils.maxIndex(a)];
        double sum = 0.0;

        for (int i = 0; i < a.length; i++) {
            sum += Math.exp(a[i] - max);
        }

        return max + Math.log(sum);
    }

    /**
     * Returns the cluster probability distribution for an instance.
     *
     * @param instance the instance to be clustered
     * @return the probability distribution
     * @throws Exception if computation fails
     */
    public double[] distributionForInstance(Instance instance) throws Exception {

        return Utils.logs2probs(logJointDensitiesForInstance(instance));
    }

    /**
     * Returns the logs of the joint densities for a given instance.
     *
     * @param inst the instance
     * @return the array of values
     * @exception Exception if values could not be computed
     */
    public double[] logJointDensitiesForInstance(Instance inst) throws Exception {

        double[] weights = logDensityPerClusterForInstance(inst);
        double[] priors = clusterPriors();

        for (int i = 0; i < weights.length; i++) {
            if (priors[i] > 0) {
                weights[i] += Math.log(priors[i]);
            } else {
                throw new IllegalArgumentException("Cluster empty!");
            }
        }
        return weights;
    }

    /**
     * Creates copies of the current clusterer. Note that this method now uses
     * Serialization to perform a deep copy, so the Clusterer object must be fully
     * Serializable. Any currently built model will now be copied as well.
     *
     * @param model an example clusterer to copy
     * @param num   the number of clusterer copies to create.
     * @return an array of clusterers.
     * @exception Exception if an error occurs
     */
    public static DensityBasedClusterer[] makeCopies(DensityBasedClusterer model, int num) throws Exception {
        if (model == null) {
            throw new Exception("No model clusterer set");
        }
        DensityBasedClusterer[] clusterers = new DensityBasedClusterer[num];
        SerializedObject so = new SerializedObject(model);
        for (int i = 0; i < clusterers.length; i++) {
            clusterers[i] = (DensityBasedClusterer) so.getObject();
        }
        return clusterers;
    }
}
